Advances in modern technology, network connectivity, processing power, convenience, and the like, support an ever increasing number of interconnected devices such as mobile devices, cell phones, tablets, smart-cars, wearable devices, etc. In turn, these advances present new challenges and create new opportunities for network operators and third party service providers to efficiently target, communicate, or otherwise exchange signals between networked devices. Indeed, modern approaches for wireless signal transmission must often account for complex conditions and dynamic factors such as network traffic, signal propagation through various media, spectrum/frequency constraints for signal transmission, and the like.
Recently, metamaterial devices have been developed to transmit and receive signals, in particular for wireless signals. Such metamaterial devices typical employ large arrays of metamaterials that are controlled to achieve desired performance metrics during operation of the metamaterials devices. However, as sizes of arrays of metamaterials integrated into metamaterial devices grow, it becomes more and more difficult to identify optimized configurations of the metamaterial devices. In particular, larger amounts of computational resources and/or time are needed to identify optimal configurations for controlling operation of the metamaterial devices to achieve an antenna system performance metric. There therefore exist needs for improved ways to control operation of metamaterials devices to achieve an antenna system performance metric during operation of the metamaterials devices. In particular, there exist needs for reducing computational resources used to control operation of metamaterials devices to achieve an antenna system performance metric during operation of the metamaterials devices.
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